Abstract

The effectiveness of refined interferometric synthetic aperture radar (InSAR) filter (refined filter) was validated using both simulated and real interferometric data. However, the threshold as a key parameter in the refined filter is determined by repeated attempts, and the deterministic method has some disadvantages, such as strong subjectivity, long time consuming, and bad adaptation. This letter makes full use of the robustness of inverse distance weighting (IDW) to simplify the refined filter. In the proposed filter, using an $11 \times 11$ window and an improved IDW, the computational burden of $| {\langle {e^{j\psi _{z}}} \rangle } |$ for 16 windows per pixel is avoided, and the need for setting the threshold is eliminated. From the beginning, the initial window angle is determined using four preprocessing windows. The filtering direction of the center pixel is affected by the initial window angle of each pixel, the degree of homogeneity of each pixel, and the distance of the pixel from the center pixel in the $11\times 11$ window. The improved weighting method is then used to further refine the window angle of the center pixel. Numerical experiments by simulated and real InSAR data were used to validate the proposed approach. By comparison, the proposed filter greatly improves the efficiency of the refined filter and exhibits the superiority in filtering performance compared to commonly used filters, particularly for regions of low coherence, high-coherence-gradient, and high-phase gradient.

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